Cameras, visible and infrared, are currently being utilized in a wide variety of applications. For example, surveillance/security cameras are commonly used to observe and track people and their activities in certain areas/locations. In automotive applications, cameras have been integrated into modern cars and trucks to help drivers and, in some cases, to monitor passengers in case of an accident. In military applications, a Forward Looking Infrared (FLIR) camera is used to observe a scene or to track a target. Other applications include industrial/structural inspection, nondestructive-testing, thermo-graphic inspection, thermal infrared imaging, night vision, remote temperature measurement, aerospace imaging, multispectral imaging, unmanned vehicle payloads, spectroscopy, firefighting, transportation, etc.
The heart of the camera is an electronic circuit (i.e., a sensor array) that captures images and provides corresponding digital values for each pixel. The performance of the sensor array is essential to the performance of the camera as a system or device. FIG. 1 is a simplified diagram of a conventional pixel sensor 100. A photoconductive diode (photo detector) produces a photo-induced current (Iph) 102, also known as “photocurrent”, that is proportional to the amount of light 101 incident on the diode. When no light is incident on the diode, some leakage current (Idc) 103, also referred to as dark current, will flow through the diode. Total current (Itotal) 104 equals photo-induced current (Iph) 102 plus dark current (Idc) 103 per Kirchoff's current law. A current to voltage convertor/amplifier 105 converts the total current (Itotal) 104 to an analog voltage (Vtotal) 106. An analog-to-digital convertor (ADC) 107 then converts this analog voltage (Vtotal) 106 and correspondingly produces a digital signal, i.e., pixel value (Pvalue) 108.
Most imagers operate in a direct-integration mode where photocurrent is integrated over a capacitor. In its simplest and most area efficient form, integration is performed onto the photodiode parasitic capacitance. Many sensor arrays, including most of the infrared ones, use an external capacitor as the integrator. The accumulated charge is read out at the end of integration time. High integration time is desirable because it increases the accuracy of the estimated photocurrent. However, integration time cannot be made arbitrarily long due to integrator saturation and scene motion considerations. Frame rate also limits integration time.
The integrator outputs electrical signals representing the intensity of the image captured by the sensor array, i.e., the imager or the image sensor. It is important that the image sensor be usable under a variety of lighting conditions because the wider the variety of lighting conditions under which the image sensor is usable the better the image quality. Consequently, the quality of an imaging system is mainly measured by the image sensor's dynamic range and its ability to mask noises, i.e., its signal-to-noise ratio (SNR), under low light conditions.
Generally, signal-to-Noise Ratio (SNR) is the ratio of the signal power over the noise power. Dynamic range is the ratio of the maximum non-saturating signal to the minimum detectable signal (i.e., signal with SNR=1). The dynamic range of an image sensor measures how wide a range of lighting the sensor can accurately capture. For example, a scene including both a tree lit by bright sunlight and a person standing under the tree has a high dynamic range. This high dynamic range makes it difficult for the image sensor, such as one used in a camera, a video recorder, or a security monitor, to capture details of both the brightly lit tree and the person standing in the tree's shadow. Although in most of the applications a sufficiently high dynamic range is required, dynamic range of conventional sensor arrays (e.g., charge-coupled devices, or CCDs) is usually limited.
Several schemes have been proposed to increase the dynamic range of the sensor array, see, for example,    1. S. J. Decker et al. “A 256×256 CMOS Imaging Array with Wide Dynamic Range Pixels and Column-Parallel Digital Output” IEEE J. of Solid-State Circuits, December 1998, V. 33, pp. 2081-2091.    2. T. Lule et al. “Design and Fabrication of a High Dynamic Range Image Sensor in TFA Technology” IEEE J. of Solid-State Circuits, May 1999, V. 34, pp. 704-711.    3. W. Yang “A Wide-Dynamic Range, Low-Power Photosensor Array” IEEE Int. Solid-State Circuits Conf., San Francisco, Calif., February 1994, pp. 230-231.    4. L. G. McIlrath “A Low-Power Low-Noise Ultrawide-Dynamic-Range CMOS Imager with Pixel-Parallel A/D Conversion” IEEE J. of Solid-State Circuits, May 2001, V. 36, I. 5, pp. 846-853.    5. B. Fowler et al. “A CMOS Area Image Sensor with Pixel-Level A/D Conversion” IEEE Int. Solid-State Circuits Conf., San Francisco, Calif., February 1994, TP 13.5, pp. 226-227.    6. D. Yang et al. “A 640×512 CMOS Image Sensor with Ultrawide Dynamic Range Floating-Point Pixel-Level ADC” JSSCC, December 1999, V. 34, No. 12, pp. 1821-1834.    7. S. Kleinfelder et al. “A 10,000 Frames/s CMOS Digital Pixel Sensor” IEEE J. of Solid-State Circuits, December 2001, V. 36, No. 12, pp. 2049-2059.
All of these schemes would perform better if the required frame rate were low. The user or tracking/rendering program that uses the raw frames usually dictates the frame rate. Essentially, the incident photon flux constancy over the pixel limits the frame rate. Motion forces the required frame rate; however, a mechanical image stabilizer usually compensates fast vibrations, thereby relaxing the frame rate requirement, which, in most applications, is low (e.g., 30 Hz).
One major problem for cameras is the presence of disturbance. Disturbance is any anomaly in the constant incident photon flux on the pixel. For example, a fast temporary reflection of the sun can cause a temporary spike in the photon flux. This is a usual scenario in automotive applications. In tactical applications, laser jamming is a technique use to ruin the frames taken by the camera. For example, a one-watt carbon-dioxide laser at 10 μm creates five orders of magnitude higher photocurrent in a long-wave infrared detector than the sun. The random movement of such a laser by the target creates saturation or partial loss of information in the sensor array when it reaches the camera. A similar scenario is possible in security applications. Such events cause spikes in the incident photon flux, resulting in undesirable partial or complete loss of information.
The state-of-the-art mechanism to overcome this problem is to use a fast frame rate, high dynamic range sensor array with over-sampled frames to detect and correct such disturbances in digital domain. This technique requires a high-speed sensor array, which has a high sensitivity and high dynamic range. However, there are fundamental limitations in achieving such performance.
For example, in order to be able to detect a temperature difference of 1 mK, the maximum possible frame rate is only 25 frames per a second (=1/0.04) for a nominal long-wave infrared pixel. This low frame rate is enough for most applications; however, the disturbance frequency would require a sensor array with a substantially much higher frame rate, e.g., 10,000 frames/s.
Moreover, certain applications require averaging techniques in digital domain on over-sampled frames. This requires very high resolution in the analog-digital convertor (ADC) stage, which is extremely challenging. It is only achievable with very high power consumption.
Clearly, there is a continuing need in the art for a new pixel sensor design and architecture that offers pixel-level disturbance detection and correction without requiring the overall sensor array to have a high frame rate and that offers very high dynamic range at high speed with much lower power, bandwidth, and memory requirements.